Could universal health care coverage restrict access? The mixed effects of universal coverage on minorities' receipt of obstetric care in northern Thailand
Bibliographic record
Abstract
Background Unequal access to safe obstetric services is still a problem worldwide. I examine maternal characteristics associated with place of childbirth and the effect of Thailand's 2001 Universal Health Care Coverage (UHCC) Plan on women's access to and use of hospital-based obstetric services. Methods I analysed household data from a sample of 13 534 women included in the UNESCO Highland Peoples Survey 2010, a survey of Thai-Burma border villages. I contextualised and triangulated statistical findings with relation to interviews I conducted with highland women and Thai health officials in 2009. With hierarchical logistic regression, I compared women's use of obstetric-based services by their ethnic group, education, language, and citizenship, overall, and before and after the UHCC plan was introduced. Findings Women's odds of having given birth in a hospital were significantly lower (p<0·0001) by (unadjusted model) 80% if they are a highland ethnic minority, and (adjusted model) 64% if they do not have citizenship, 68% if they have not had any schooling (compared with having finished upper secondary school), 27% if Thai is not spoken at home, and 47% if a minority language is spoken at home. Although women are generally more likely to have given birth in hospitals after the UHCC plan, nearly all inequalities between subgroups widened after the policy change. Interviews showed that although the UHCC generally reduced health-care-related costs, it imposed tighter restrictions on public insurance coverage and hospital spending, which resulted in unequal benefits to certain subpopulations. Interpretation Despite its commitment to expanding universal health care, Thailand has not eliminated all barriers to providing equal access to obstetric care services. These findings show the mixed effects of national universal health-care coverage plans. Funding The British Embassy-Bangkok, the Canadian International Development Agency, pre-doctoral National Research Service Award Training Grant (T32 HS00023, PI: Smith), and National Institute of Child Health and Human Development Training Grant (T32 5T32AG000129-25, PD: Palloni).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".